Add: tf vs pt blog

.gitignore

@@ -179,4 +179,11 @@ cython_debug/
 **/*.csv
 **/*.jpg
 
+benchmarking/
+
+# Models
+**/*.keras
+**/*.pt
+**/*.csv
+
 benchmarking/

pyproject.toml

@@ -21,7 +21,7 @@ dependencies = [
     "pydantic >= 2.10.6",
     "torchinfo >= 1.8.0",
     "stocaching >= 0.2.0",
-    "tensorflow >= 2.19.0",
+    "tensorflow[and-cuda] >= 2.19.0",
     "matplotlib >= 3.10.1",
     "torchvision >= 0.21.0",
 ]

tfvspt/base.py

@@ -1,7 +1,5 @@
 """Benchmarking Base."""
 
-import logging
-
 import matplotlib.pyplot as plt
 import numpy as np
 

tfvspt/pt/main.py

@@ -193,7 +193,7 @@ def train(self) -> None:
 
         # save model
         st = time.time()
-        torch.jit.script(model).save(str(self.config.output / "cifar100.pt"))
+        torch.jit.script(model).save(str(self.config.output / "last.pt"))
         self._log_stats("model_saving_time", time.time() - st)
 
     def eval(self) -> dict:
@@ -202,7 +202,7 @@ def eval(self) -> dict:
 
         # load model
         st = time.time()
-        model = torch.jit.load(str(self.config.output / "cifar100.pt"))
+        model = torch.jit.load(str(self.config.output / "last.pt"))
         self._log_stats("model_loading_time", time.time() - st)
 
         # evaluate

tfvspt/tf/main.py

@@ -49,7 +49,7 @@ def plot_images(self, dataloader, name: str) -> None:
     def get_callbacks(self) -> list:
         # train history logger
         csv_logger = tf.keras.callbacks.CSVLogger(str(self.config.output /
-                                                      'cifar100_training.csv'),
+                                                      'history.csv'),
                                                   separator=",",
                                                   append=False)
         return [csv_logger]
@@ -97,7 +97,7 @@ def train(self) -> None:
 
         # save model
         st = time.time()
-        model.save(str(self.config.output / "cifar100.keras"))
+        model.save(str(self.config.output / "last.keras"))
         self._log_stats("model_saving_time", time.time() - st)
 
     def eval(self) -> dict:
@@ -107,7 +107,7 @@ def eval(self) -> dict:
         # load model
         st = time.time()
         model = tf.keras.models.load_model(
-            str(self.config.output / "cifar100.keras"))
+            str(self.config.output / "last.keras"))
         self._log_stats("model_loading_time", time.time() - st)
 
         # evaluate